Keywords

environmental modeling; agents; fields; data model; spatio-temporal data

Location

Session D1: GIS and Environmental Modeling for Decision Support

Start Date

16-6-2014 9:00 AM

End Date

16-6-2014 10:20 AM

Description

Environmental modeling involves manipulating environmental attributes represented in soft­ware by agents, fields or both, but most modeling environments are designed to be especially useful for either agent-based or field-based modeling. Agent-based and field-based modeling environments have different properties with respect to their ease of use and how well both agents and fields can be represented and manipulated. Most agent-based modeling environments require the modeler to use a general purpose object oriented programming language like Java to express models, while field-based modeling environments often implement a high level, domain specific imperative language based on map algebra, or extent a general purpose scripting language. Because of this, field-based models are more easily defined by domain experts than agent-based models. On the other hand, because a lower level language is used, agent-based modeling environments are more easily extended by missing functionality, like support for fields, while in general, field-based modeling environments lack support for defining agents. We are working on a new environmental modeling environment which is designed from the ground up for manipulating both agents and fields. Our goal is to combine the advantages of current agent-based and field-based modeling environments. For this, a conceptual data model is developed which is capable of storing both agent and field data, and which is a superset of the traditionally separate data models for agents and fields. Given this data model a high level domain specific imperative language is designed which enables domain experts to define combined agent­ and field-based models.

 
Jun 16th, 9:00 AM Jun 16th, 10:20 AM

An Environmental Modeling Language for Agents and Fields

Session D1: GIS and Environmental Modeling for Decision Support

Environmental modeling involves manipulating environmental attributes represented in soft­ware by agents, fields or both, but most modeling environments are designed to be especially useful for either agent-based or field-based modeling. Agent-based and field-based modeling environments have different properties with respect to their ease of use and how well both agents and fields can be represented and manipulated. Most agent-based modeling environments require the modeler to use a general purpose object oriented programming language like Java to express models, while field-based modeling environments often implement a high level, domain specific imperative language based on map algebra, or extent a general purpose scripting language. Because of this, field-based models are more easily defined by domain experts than agent-based models. On the other hand, because a lower level language is used, agent-based modeling environments are more easily extended by missing functionality, like support for fields, while in general, field-based modeling environments lack support for defining agents. We are working on a new environmental modeling environment which is designed from the ground up for manipulating both agents and fields. Our goal is to combine the advantages of current agent-based and field-based modeling environments. For this, a conceptual data model is developed which is capable of storing both agent and field data, and which is a superset of the traditionally separate data models for agents and fields. Given this data model a high level domain specific imperative language is designed which enables domain experts to define combined agent­ and field-based models.